"The Fed's Real Reaction Function: Monetary Policy, Inflation, Unemployment, Inequality-and Presidential Politics"

Using a VAR model of the American economy from 1984 to 2003, we find that, contrary to official claims, the Federal Reserve does not target inflation or react to "inflation signals." Rather, the Fed reacts to the very "real" signal sent by unemployment, in a way that suggests that a baseless fear of full employment is a principal force behind monetary policy. Tests of variations in the workings of a Taylor Rule, using dummy variable regressions, on data going back to 1969 suggest that after 1983 the Federal Reserve largely ceased reacting to inflation or high unemployment, but continued to react when unemployment fell "too low." Further, we find that monetary policy (measured by the yield curve) has significant causal impact on pay inequality-a domain where the Fed refuses responsibility. Finally, we test whether Federal Reserve policy has exhibited a pattern of partisan bias in presidential election years, with results that suggest the presence of such bias, after controlling for the effects of inflation and unemployment.

Tomato Expression Database (TED): a suite of data presentation and analysis tools

The Tomato Expression Database (TED) includes three integrated components. The Tomato Microarray Data Warehouse serves as a central repository for raw gene expression data derived from the public tomato cDNA microarray. In addition to expression data, TED stores experimental design and array information in compliance with the MIAME guidelines and provides web interfaces for researchers to retrieve data for their own analysis and use. The Tomato Microarray Expression Database contains normalized and processed microarray data for ten time points with nine pair-wise comparisons during fruit development and ripening in a normal tomato variety and nearly isogenic single gene mutants impacting fruit development and ripening. Finally, the Tomato Digital Expression Database contains raw and normalized digital expression (EST abundance) data derived from analysis of the complete public tomato EST collection containing >150 000 ESTs derived from 27 different non-normalized EST libraries. This last component also includes tools for the comparison of tomato and Arabidopsis digital expression data. A set of query interfaces and analysis, and visualization tools have been developed and incorporated into TED, which aid users in identifying and deciphering biologically important information from our datasets. TED can be accessed at

The molecular control of tomato fruit quality traits: the trade off between visual attributes, shelf life and nutritional value

Tomato (Solanum lycopersicum) is an established model to study fleshy fruit development and ripening and is an important crop in terms of its economic and nutritional value. Tomato fruit quality is a function of metabolite content which is prone to physiological changes related to fruit development and ripening. It has been described some ripening tomato mutants, delayed fruit deterioration (DFD), non-ripening (NOR) and ripening-inhibitor (RIN) which substantially extend “shelf life” in tomato for up to several months when defined in terms of softening, water loss and resistance to postharvest biotic infection. However, it is not known whether this extension in “shelf life” is in fact a desirable objective from the perspective of nutritional quality of the fruits. The aim of this work was to use a metabolomics approach join to genomic tools to characterize compositional changes (sugars, amino acids, organic acids and carotenoids) of non-softening tomato mutants reported (DFD, NOR and RIN) in comparison with the normally softening fruits (Ailsa Craig and M82) during ripening and postharvest shelf-life. Important results related with ripening gene expression and metabolic evolutions are shown

A Comparison of Nuggets and Clusters for Evaluating Timeline Summaries

There is growing interest in systems that generate timeline summaries by filtering high-volume streams of documents to retain only those that are relevant to a particular event or topic. Continued advances in algorithms and techniques for this task depend on standardized and reproducible evaluation methodologies for comparing systems. However, timeline summary evaluation is still in its infancy, with competing methodologies currently being explored in international evaluation forums such as TREC. One area of active exploration is how to explicitly represent the units of information that should appear in a 'good' summary. Currently, there are two main approaches, one based on identifying nuggets in an external 'ground truth', and the other based on clustering system outputs. In this paper, by building test collections that have both nugget and cluster annotations, we are able to compare these two approaches. Specifically, we address questions related to evaluation effort, differences in the final evaluation products, and correlations between scores and rankings generated by both approaches. We summarize advantages and disadvantages of nuggets and clusters to offer recommendations for future system evaluation

The impact of sphingosine-1-phosphate receptor modulators on COVID-19 and SARS-CoV-2 vaccination.

BACKGROUND: Sphingosine-one phosphate receptor (S1PR) modulation inhibits S1PR1-mediated lymphocyte migration, lesion formation and positively-impacts on active multiple sclerosis (MS). These S1PR modulatory drugs have different: European Union use restrictions, pharmacokinetics, metabolic profiles and S1PR receptor affinities that may impact MS-management. Importantly, these confer useful properties in dealing with COVID-19, anti-viral drug responses and generating SARS-CoV-2 vaccine responses. OBJECTIVE: To examine the biology and emerging data that potentially underpins immunity to the SARS-CoV-2 virus following natural infection and vaccination and determine how this impinges on the use of current sphingosine-one-phosphate modulators used in the treatment of MS. METHODS: A literature review was performed, and data on infection, vaccination responses; S1PR distribution and functional activity was extracted from regulatory and academic information within the public domain. OBSERVATIONS: Most COVID-19 related information relates to the use of fingolimod. This indicates that continuous S1PR1, S1PR3, S1PR4 and S1PR5 modulation is not associated with a worse prognosis following SARS-CoV-2 infection. Whilst fingolimod use is associated with blunted seroconversion and reduced peripheral T-cell vaccine responses, it appears that people on siponimod, ozanimod and ponesimod exhibit stronger vaccine-responses, which could be related notably to a limited impact on S1PR4 activity. Whilst it is thought that S1PR3 controls B cell function in addition to actions by S1PR1 and S1PR2, this may be species-related effect in rodents that is not yet substantiated in humans, as seen with bradycardia issues. Blunted antibody responses can be related to actions on B and T-cell subsets, germinal centre function and innate-immune biology. Although S1P1R-related functions are seeming central to control of MS and the generation of a fully functional vaccination response; the relative lack of influence on S1PR4-mediated actions on dendritic cells may increase the rate of vaccine-induced seroconversion with the newer generation of S1PR modulators and improve the risk-benefit balance IMPLICATIONS: Although fingolimod is a useful asset in controlling MS, recently-approved S1PR modulators may have beneficial biology related to pharmacokinetics, metabolism and more-restricted targeting that make it easier to generate infection-control and effective anti-viral responses to SARS-COV-2 and other pathogens. Further studies are warranted

Myopia in late adolescence and subsequent multiple sclerosis among men

BACKGROUND: Risk factors such as low vitamin D level has been implicated in the etiology of multiple sclerosis (MS) and may be relevant to myopia, such that there may be an association between myopia and MS. METHODS: Using linked Swedish national register data, we conducted a cohort study of men who were born in Sweden between 1950 and 1992, lived in Sweden between 1990 and 2018, and enrolled in military conscription assessment (n = 1,847,754). Myopia was defined based on the spherical equivalent refraction measured at conscription assessment, around age 18 years. Multiple sclerosis was identified using the Patient Register. Cox regression produced hazard ratios (HR) with 95% confidence intervals (95% CI), with adjustment for demographic and childhood socioeconomic characteristics and residential region. Due to changes in the assessment of refractive error, the analysis was stratified into two groups by the year of conscription assessment: 1969-1997 and 1997-2010. RESULTS: Among 1,559,859 individuals during a maximum of 48 years of follow-up from age 20 to 68 years (44,715,603 person-years), there were 3,134 MS events, and the incidence rate 7.0 (95% CI [6.8, 7.3] per 100,000 person-years). Among individuals with conscription assessments during 1997-2010, there were 380 MS events. There was no evidence of an association between myopia and MS, with HR 1.09 (95% CI 0.83, 1.43). Among individuals who underwent conscription assessment in 1969-1997, there were 2754 MS events. After adjusting for all covariates, there was no evidence of an association between myopia and MS (HR 0.99 [95% CI 0.91, 1.09]). CONCLUSION: Myopia in late adolescence is not associated with a subsequent raised risk of MS and thus there does not appear to be important shared risk factors

Virus-induced gene complementation reveals a transcription factor network in modulation of tomato fruit ripening

Plant virus technology, in particular virus-induced gene silencing, is a widely used reverse- and forward-genetics tool in plant functional genomics. However the potential of virus technology to express genes to induce phenotypes or to complement mutants in order to understand the function of plant genes is not well documented. Here we exploit Potato virus X as a tool for virus-induced gene complementation (VIGC). Using VIGC in tomato, we demonstrated that ectopic viral expression of LeMADS-RIN, which encodes a MADS-box transcription factor (TF), resulted in functional complementation of the non-ripening rin mutant phenotype and caused fruits to ripen. Comparative gene expression analysis indicated that LeMADS-RIN up-regulated expression of the SBP-box (SQUAMOSA promoter binding protein-like) gene LeSPL-CNR, but down-regulated the expression of LeHB-1, an HD-Zip homeobox TF gene. Our data support the hypothesis that a transcriptional network may exist among key TFs in the modulation of fruit ripening in tomato

*omeSOM: a software for clustering and visualization of transcriptional and metabolite data mined from interspecific crosses of crop plants

Background: Modern biology uses experimental systems that involve the exploration of phenotypic variation as a result of the recombination of several genomes. Such systems are useful to investigate the functional evolution of metabolic networks. One such approach is the analysis of transcript and metabolite profiles. These kinds of studies generate a large amount of data, which require dedicated computational tools for their analysis.Results: This paper presents a novel software named *omeSOM (transcript/metabol-ome Self Organizing Map) that implements a neural model for biological data clustering and visualization. It allows the discovery of relationships between changes in transcripts and metabolites of crop plants harboring introgressed exotic alleles and furthermore, its use can be extended to other type of omics data. The software is focused on the easy identification of groups including different molecular entities, independently of the number of clusters formed. The *omeSOM software provides easy-to-visualize interfaces for the identification of coordinated variations in the co-expressed genes and co-accumulated metabolites. Additionally, this information is linked to the most widely used gene annotation and metabolic pathway databases.Conclusions: *omeSOM is a software designed to give support to the data mining task of metabolic and transcriptional datasets derived from different databases. It provides a user-friendly interface and offers several visualization features, easy to understand by non-expert users. Therefore, *omeSOM provides support for data mining tasks and it is applicable to basic research as well as applied breeding programs. The software and a sample dataset are available free of charge at http://sourcesinc.sourceforge.net/omesom/.Fil: Milone, Diego Humberto. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Departamento de Informática. Laboratorio de Investigaciones en Señales e Inteligencia Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Stegmayer, Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Centro de Investigación y Desarrollo de Ingeniería en Sistemas de Información; ArgentinaFil: Kamenetzky, Laura. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: López, Mariana. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; ArgentinaFil: Lee, Je M.. Cornell University; Estados UnidosFil: Giovannoni, James J.. Cornell University; Estados UnidosFil: Carrari, Fernando Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentin